Use of Simulated Atrophy for Performance Analysis of Brain Atrophy Estimation Approaches

Abstract

Abstract.In this paper, we study the performance of popular brain atrophy estimation algorithms using a simulated gold standard. The availability of a gold standard facilitates a sound evaluation of the measures of atrophy estimation, which is otherwise complicated. Firstly, we propose an approach for the construction of a gold standard. It involves the simulation of a realistic brain tissue loss based on the estimation of a topology preserving B-spline based deformation fields. Using this gold standard, we present an evaluation of three standard brain atrophy estimation methods (SIENA, SIENAX and BSI) in the presence of bias field inhomogeneity and noise. The effect of brain lesion load on the measured atrophy is also evaluated. Our experiments demonstrate that SIENA, SIENAX and BSI show a deterioration in their performance in the presence of bias field inhomogeneity and noise. The observed mean absolute errors in the measured Percentage of Brain Volume Change (PBVC) are 0.35% ± 0.38, 2.03% ± 1.46 and 0.91% ± 0.80 for SIENA, SIENAX and BSI, respectively, for simulated whole brain atrophies in the range 0 − 1%.

Adaptive image segmentation for robust measurement of longitudinal brain tissue change

“…, gray matter, white matter, and cerebrospinal fluid – CSF). In addition its performance has been shown to deteriorate in the presence of noise or MRI field non-uniformities [9]. Another approach uses a true “4-D” image framework to ensure that tissue classification of an image voxel is consistent with its neighbor locations in both space and time [10].…”